Allocation of service provider resources based on a capacity to provide the service

ABSTRACT

An example includes one or more devices may include one or more memories and one or more processors, communicatively coupled with at least one of the one or more memories, to identify a service that is provided within a region; identify a model that is associated with the service, the model having been trained based on consumer profile data, service provider data, and historical information; determine a current demand associated with the service in the region; predict, using the model and based on the current demand associated with the service, a future demand for the service during a time period; determine a current capacity to provide the service based on real-time service provider information associated with service providers that are providing the service in the region; and perform an action associated with the service based on the future demand for the service and the current capacity to provide the service.

RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.15/847,146, filed Dec. 19, 2017, which is incorporated herein byreference.

BACKGROUND

In many instances, organizations employ staff members (e.g., employees)to provide a service. Additionally, or alternatively, organizations mayuse independent contractors, and/or the like to provide the service. Insome instances, organizations may utilize machines, such as vehicles,unmanned aerial vehicles (UAVs) (e.g., drones), kiosks, self-serveterminals, and/or the like to provide a service.

SUMMARY

According to some implementations, one or more devices may include oneor more memories and one or more processors, communicatively connectedto at least one of the one or more memories, to identify a service thatis provided within a region; identify a model that is associated withthe service, the model having been trained based on consumer profiledata relating to consumers that have received the service in the region,service provider data associated with service providers that haveprovided the service in the region, and historical informationassociated with providing the service in the region; determine a currentdemand associated with the service in the region; predict, using themodel and based on the current demand associated with the service, afuture demand for the service during a time period; determine a currentcapacity to provide the service based on real-time service providerinformation associated with service providers that are providing theservice in the region; and perform an action associated with the servicebased on the future demand for the service and the current capacity toprovide the service.

According to some implementations, a non-transitory computer-readablemedium storing instructions that, when executed by one or moreprocessors, cause the one or more processors to: identify a service thatis provided within a region; train a model that is associated with theservice based on: consumer trends in consumer profile data relating toconsumers that have received the service in the region, service providertrends in service provider data associated with service providers thathave provided the service in the region, and historical trends inhistorical information associated with providing the service in theregion; determine a current demand for the service in the region;predict, using the model and based on the current demand for theservice, a future demand for the service during a time period; determinea current capacity to provide the service during the time period basedon real-time service provider information associated with serviceproviders that are providing the service in the region; and perform anaction associated with the service based on the future demand for theservice and the current capacity to provide the service during the timeperiod.

According to some implementations, a method may include identifying, byone or more devices, a service that is provided within a region;obtaining, by one or more devices, a model that is associated with theservice, the model having been trained based on consumer profile datarelating to consumers that have received the service in the region,service provider data associated with service providers that haveprovided the service in the region, and historical informationassociated with providing the service in the region; determining, by theone or more devices, a current demand associated with the service in theregion; predicting, by the one or more devices, using the model, andbased on the current demand associated with the service, a future demandfor the service during a time period; determining, by the one or moredevices, a current capacity to provide the service based on real-timeservice provider information for devices associated with particularservice providers that are providing the service in the region;comparing, via the one or more devices, the current capacity to providethe service and the future demand for the service to determine whetherthe current capacity is capable of meeting the future demand for theservice; and performing, via the one or more devices, an actionassociated with the service based whether the current capacity iscapable of meeting the future demand for the service.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A and 1B are diagrams of an overview of an example implementationdescribed herein;

FIG. 2 is a diagram of an example environment in which systems and/ormethods, described herein, may be implemented;

FIG. 3 is a diagram of example components of one or more devices of FIG.2;

FIG. 4 is a flow chart of an example process for allocating serviceprovider resources based on a capacity to provide the service; and

FIG. 5 is a flow chart of another example process for allocating serviceprovider resources based on a capacity to provide the service.

DETAILED DESCRIPTION

The following detailed description of example implementations refers tothe accompanying drawings. The same reference numbers in differentdrawings may identify the same or similar elements.

In many instances, a service provider organization (e.g., a financialinstitution (e.g., a bank, a credit union, and/or the like), ahealthcare organization (e.g., a hospital, a clinic, an urgent carecenter, and/or the like), a law firm, an accounting firm, and/or thelike) staffs service providers (e.g., individuals, such as employees,independent contractors, and/or the like) at one or more servicelocations (e.g., a bank branch, a hospital, firm offices, and/or thelike). Accordingly, an amount of service providers employed by aparticular service provider organization and/or an amount of serviceprovider equipment used to provide the service may be limited to anamount of space available at the one or more service locations of theservice provider organization. Furthermore, location(s) of the one ormore service locations may limit a service provider organization'sability to provide a service to within a certain range of the servicelocation(s) of the service provider organization.

As such, in many instances, during particular time periods, the serviceprovider organizations may be understaffed and/or underequipped toprovide a particular service. For example, during tax season, banks oraccounting firms may need to temporarily hire additional staff and,during holidays, retailers, transportation companies, and/or other typesof organizations may need to do the same. As another example, during anatural disaster, in general for both service provider and consumer,resources can be drastically limited as an entire region attempts torecover from the natural disaster. Some implementations described hereinprovide a marketplace platform to facilitate adjusting an amount ofservice provider resources available to provide a service. The availableservice provider resources may include service providers (e.g.,individuals or personnel that provide the service or facilitateproviding the service, such as employees of the service providerorganization, independent contractors, and/or the like) and/or serviceprovider equipment (e.g., one or more machines that provide the serviceor facilitate providing the service) that can be made available toprovide a service or withdraw from providing the service, during aparticular time period, according to a predicted demand for the service.

According to some implementations described herein, a model may betrained based on a set of data (e.g., consumer related data, serviceprovider related data, and/or historical information) and used topredict a future demand for a service during a particular time period.In some implementations, a current demand for the service may bemonitored and/or analyzed to predict the future demand for the service.Further, based on the future demand and a capacity to provide a service,a marketplace platform may facilitate increasing or decreasing serviceprovider resources in accordance with the future demand. For example,the marketplace platform may have access to a service providerorganization's resources, availability of additional service providers(such as employees (e.g., remote employees, off duty employees, and/orthe like), independent contractors that are capable of providing theservice or potentially capable of providing the service, and/or thelike), additional available service provider equipment (e.g., autonomous(or semi-autonomous) vehicles (e.g., autonomous cars, an autonomoustrucks, an autonomous semi-tractors or autonomous semi-tractor trailercombinations, and/or the like), an unmanned aerial vehicle (UAV) (e.g.,a drone), portable kiosks (e.g., kiosks that may be included within orattached to one or more autonomous vehicles), transaction terminals,and/or the like) for use in meeting the future demand.

Accordingly, the marketplace platform may enable the service providerorganization to quickly and efficiently adjust service providerresources to meet a demand for a service. As such, service providerorganizations may avoid turning away consumers (e.g., and losingprofits, losing good will, losing an ability to meet a consumer's needs(which can be critical)). Further, some implementations herein may avoidwasting computing resources due to having an unnecessary amount ofequipment available. In some implementations, networking resources maybe conserved due to unnecessary communications over a network, due toavoiding receiving requests for service from consumers, due to avoidingreceiving requests from service providers to be available to provide aservice, and/or the like. Additionally, or alternatively, powerresources may be conserved due to avoiding unnecessary equipment frombeing powered on and/or in use.

FIGS. 1A and 1B are diagrams of an overview of an example implementation100 described herein. In example implementation 100 of FIGS. 1A and 1B,a marketplace platform facilitates allocation of resources to provide aservice based on a predicted demand for the service.

As shown in FIG. 1A, and by reference number 110, the marketplaceplatform obtains information associated with a service. In such cases,the information associated with the service may be used to indicate ademand. For example, as shown in FIG. 1A, a consumer data structure mayinclude M consumer profiles (M≥1) corresponding to M consumers of aparticular service provider organization. Such consumer profiles mayinclude consumer data for a particular region (e.g., a town or city, acounty, a state, and/or the like) or service location of a serviceprovider organization. As shown in FIG. 1A, the consumer data mayidentify a number of times that the M consumers received a particularservice, when the service was received, what service was received,and/or detailed information about the provided service.

Furthermore, as shown in FIG. 1A, the marketplace platform may receivehistorical information associated with the service. In someimplementations, the historical information associated with the servicemay be based on a region that is larger than the region associated withthe consumer data (e.g., state wide region, a country wide region). Thehistorical information may include a service log for the service, whichmay represent or indicate information corresponding to occurrences ofwhen the service was provided.

As further shown in FIG. 1A, the marketplace platform receivesinformation associated with the service from service location monitorsand environmental monitors. The service location monitors andenvironmental monitors may be associated with a same region of a serviceprovider organization as the consumer data of the consumer datastructure.

In some implementations, the service location monitors of exampleimplementation 100 may include transaction terminals (e.g., paymentterminals, kiosks, self-service terminals, and/or the like) thatfacilitate providing the service. A status of the transaction terminals,indicating whether the transaction terminals are active, idle, orpowered off, may be obtained by the marketplace platform. Additionally,or alternatively, the service location monitors may include camerasand/or sensors that may provide images or data that can be analyzed toidentify a number of individuals (e.g., consumers, service providers,and/or the like) at the location. The environmental monitors may includedevices that monitor environmental factors associated with or thataffect the service. For example, the environment monitors may includeone or more devices or feeds providing weather-related information,traffic-related information, social media activity or social mediatrends, breaking news, and/or the like. Accordingly, marketplaceplatform may use the obtained information (e.g., the status of thetransaction terminals, the number of people at a service location, theenvironmental factors, and/or the like) from the service locationmonitors and the environmental monitors to determine a current demand orfuture demand for a service.

As shown in FIG. 1B, and by reference number 120, the marketplaceplatform determines that additional service provider resources (e.g.,additional service providers and/or additional service providerequipment) are needed to provide the service based on the obtainedinformation. For example, from the obtained information, the marketplaceplatform may predict a future demand for the service (e.g., using amodel that is trained from the obtained data) during a particular timeperiod (e.g., an upcoming week, an upcoming month, an upcoming season,and/or the like). In some implementations, the marketplace platform maycompare the future demand to a capacity for the service providerorganization to provide the service (e.g., based on information from theservice location monitors, based on scheduling information associatedwith service providers or service provider equipment and/or the like).

As further shown in FIG. 1B, and by reference number 130, themarketplace platform identifies available service provider resources(e.g., service providers and/or service provider equipment) to providethe service using service provider data. For example, as shown, themarketplace platform may refer to a service provider marketplace datastructure that includes information associated with service providersand/or service provider equipment that may or may not be associated witha particular service provider organization. Accordingly, the marketplaceplatform may identify additional service providers and/or serviceprovider resources to facilitate providing the service during the timeperiod associated with the future demand. As shown, the service providermarketplace data structure may indicate qualifications and/oravailability of the service providers and type and/or availability ofthe equipment.

As further shown in FIG. 1B, and by reference number 140, themarketplace platform communicates with service provider resources, basedon the service provider information in the service provider marketplacedata structure, to facilitate providing the service. For example, themarketplace platform may identify one or more available serviceproviders, and send a notification to a user device of the serviceprovider indicating that the service provider is to provide the serviceduring the time period. In some implementations, the notification mayinclude a request to provide the service (which may be accepted ordenied by the service provider). In some implementations, thenotification may provide qualification information associated withproviding the service (e.g., so that the service provider may becomequalified to provide the service before the time period associated withthe future demand). Additionally, or alternatively, the marketplaceplatform may communicate with the service provider equipment. Forexample, the marketplace platform may control or facilitate controllingthe service provider equipment to be available to provide the serviceduring the time period associated with the future demand. In someimplementations, a notification may be sent to a service provider to usethe service provider equipment and/or retrieve the service providerequipment to provide the service during the time period associated withthe future demand for the service.

Accordingly, the marketplace platform of example implementation 100enables a service provider organization to scale service providerresources appropriately based on predicted future demand for a service.As such, the marketplace platform may be used to allocate appropriateamounts of resources to provide a service to ensure that consumers'needs for the service are met and/or to ensure that resources (e.g.computing resources, network resources, power resources, hardwareresources, equipment, and/or the like) are conserved by allocating theappropriate amount of resources (i.e., over allocation of resources canbe avoided).

As indicated above, FIGS. 1A and 1B are provided merely as an example.Other examples are possible and may differ from what was described withregard to FIGS. 1A and 1B.

FIG. 2 is a diagram of an example environment 200 in which systemsand/or methods, described herein, may be implemented. As shown in FIG.2, environment 200 may include a service provider device 210, one ormore monitoring devices 220-1 through 220-N (N≥1) (hereinafter referredto collectively as “monitoring devices 220,” and individually as“monitoring device 220”), a marketplace platform 225 hosted within acloud computing environment 230, and a network 240. Devices ofenvironment 200 may interconnect via wired connections, wirelessconnections, or a combination of wired and wireless connections.

Service provider device 210 includes one or more devices capable ofreceiving, generating, storing, processing, and/or providing informationassociated with identifying a service, providing a service, and/ordetermining a status of a service according to some implementationsdescribed herein. For example, service provider device 210 may include auser device with a communication and/or computing device, such as amobile phone (e.g., a smart phone, a radiotelephone, etc.), a laptopcomputer, a tablet computer, a handheld computer, a gaming device, awearable communication device (e.g., a smart wristwatch, a pair of smarteyeglasses, etc.), or a similar type of device. Further, serviceprovider device 210 may include a device capable of providing a service.For example, service provider device 210 may include an autonomous (orsemi-autonomous) vehicle (e.g., an autonomous car, an autonomous truck,an autonomous semi-tractor or autonomous semi-tractor trailercombination, and/or the like), a unmanned aerial vehicle (UAV) (e.g., adrone), a portable kiosk (e.g., a kiosk that may be included within orattached to an autonomous vehicle), a transaction terminal, and/or anyother type of device capable of providing a service according toimplementations described herein.

Monitoring device 220 includes one or more devices capable of receiving,generating, storing, processing, and/or providing information associatedwith a status of a service and/or demand for a service. For example,monitoring device 220 may include a communication device and a computingdevice, such as a transaction terminal (e.g., a payment terminal, akiosk terminal, a self-service terminal, an automated teller machine(ATM) terminal, and/or the like), a camera, a sensor, a weather monitor,a traffic monitor, a social media feed (e.g., a social media activityfeed, a social media trend feed, and/or the like), a breaking news feed,and/or the like. As such, monitoring device 220 may communicate withmarketplace platform 225 to provide information associated with a statusof a service and/or a demand for a service.

Marketplace platform 225 includes one or more devices (e.g., computingresources 235) capable of monitoring a service according toimplementations described herein. For example, marketplace platform 225may be capable of monitoring the service via monitoring devices 220;determining a current demand for the service based on information fromthe monitoring devices; and/or identifying, using, or training a modelused to predict a future demand for the service. In someimplementations, marketplace platform 225 may indicate or provideinformation associated with a service to service provider device 210.For example, marketplace platform 225 may send instructions forproviding a service to service provider device 210, may sendinstructions to control service provider device 210 to be available toprovide the service (e.g., during a particular time period and/or at aparticular location).

Cloud computing environment 230 includes an environment that deliverscomputing as a service, whereby shared resources, services, and/or thelike may be provided to service provider device 210, and/or monitoringdevices 220. Cloud computing environment 230 includes an environmentthat hosts marketplace platform 225. Cloud computing environment 230 mayprovide computation, software, data access, storage, and/or otherservices that do not require end-user knowledge of a physical locationand/or configuration of a system and/or a device that delivers theservices. As shown, cloud computing environment 230 may include a groupof computing resources 235 (which may be referred to herein individuallyas computing resource 235).

Notably, while implementations described herein describe marketplaceplatform 225 as being hosted in cloud computing environment 230, in someimplementations, marketplace platform 225 may not be cloud-based (i.e.,may be implemented outside of a cloud computing environment) or may bepartially cloud-based.

Computing resource 235 includes one or more personal computers,workstation computers, server devices, or another type of computationand/or communication device. In some implementations, one or morecomputing resources 235 may host marketplace platform 225. The cloudresources may include compute instances executing in computing resource235, storage devices provided in computing resource 235, data transferdevices provided by computing resource 235, etc. In someimplementations, computing resource 235 may communicate with othercomputing resources 235 via wired connections, wireless connections, ora combination of wired and wireless connections.

As further shown in FIG. 2, computing resource 235 may include a groupof cloud resources, such as one or more applications (“APPs”) 235-1, oneor more virtual machines (“VMs”) 235-2, virtualized storage (“VSs”)235-3, one or more hypervisors (“HYPs”) 235-4, or the like.

Application 235-1 includes one or more software applications that may beprovided to or accessed by service provider device 210. Application235-1 may eliminate a need to install and execute the softwareapplications on service provider device 210. For example, application235-1 may include software associated with marketplace platform 225and/or any other software capable of being provided via cloud computingenvironment 230. In some implementations, one application 235-1 maysend/receive information to/from one or more other applications 235-1,via virtual machine 235-2.

Virtual machine 235-2 includes a software implementation of a machine(e.g., a computer) that executes programs like a physical machine.Virtual machine 235-2 may be either a system virtual machine or aprocess virtual machine, depending upon use and degree of correspondenceto any real machine by virtual machine 235-2. A system virtual machinemay provide a complete system platform that supports execution of acomplete operating system (“OS”). A process virtual machine may executea single program, and may support a single process. In someimplementations, virtual machine 235-2 may execute on behalf of a user(e.g., via service provider device 210), and may manage infrastructureof cloud computing environment 230, such as data management,synchronization, or long-duration data transfers.

Virtualized storage 235-3 includes one or more storage systems and/orone or more devices that use virtualization techniques within thestorage systems or devices of computing resource 235. In someimplementations, within the context of a storage system, types ofvirtualizations may include block virtualization and filevirtualization. Block virtualization may refer to abstraction (orseparation) of logical storage from physical storage so that the storagesystem may be accessed without regard to physical storage orheterogeneous structure. The separation may permit administrators of thestorage system flexibility in how the administrators manage storage forend users. File virtualization may eliminate dependencies between dataaccessed at a file level and a location where files are physicallystored. This may enable optimization of storage use, serverconsolidation, and/or performance of non-disruptive file migrations.

Hypervisor 235-4 provides hardware virtualization techniques that allowmultiple operating systems (e.g., “guest operating systems”) to executeconcurrently on a host computer, such as computing resource 235.Hypervisor 235-4 may present a virtual operating platform to the guestoperating systems, and may manage the execution of the guest operatingsystems. Multiple instances of a variety of operating systems may sharevirtualized hardware resources.

Network 240 includes one or more wired and/or wireless networks. Forexample, network 240 may include a cellular network (e.g., a long-termevolution (LTE) network, a code division multiple access (CDMA) network,a 3G network, a 4G network, a 5G network, another type of nextgeneration network, etc.), a public land mobile network (PLMN), a localarea network (LAN), a wide area network (WAN), a metropolitan areanetwork (MAN), a telephone network (e.g., the Public Switched TelephoneNetwork (PSTN)), a private network, an ad hoc network, an intranet, theInternet, a fiber optic-based network, a cloud computing network, or thelike, and/or a combination of these or other types of networks.

The number and arrangement of devices and networks shown in FIG. 2 areprovided as an example. In practice, there may be additional devicesand/or networks, fewer devices and/or networks, different devices and/ornetworks, or differently arranged devices and/or networks than thoseshown in FIG. 2. Furthermore, two or more devices shown in FIG. 2 may beimplemented within a single device, or a single device shown in FIG. 2may be implemented as multiple, distributed devices. Additionally, oralternatively, a set of devices (e.g., one or more devices) ofenvironment 200 may perform one or more functions described as beingperformed by another set of devices of environment 200.

FIG. 3 is a diagram of example components of a device 300. Device 300may correspond to service provider device 210, monitoring device 220,marketplace platform 225, or computing resource 235. In someimplementations, service provider device 210, monitoring device 220,marketplace platform 225, and/or computing resource 235 may include oneor more devices 300 and/or one or more components of device 300. Asshown in FIG. 3, device 300 may include a bus 310, a processor 320, amemory 330, a storage component 340, an input component 350, an outputcomponent 360, and a communication interface 370.

Bus 310 includes a component that permits communication among thecomponents of device 300. Processor 320 is implemented in hardware,firmware, or a combination of hardware and software. Processor 320 is acentral processing unit (CPU), a graphics processing unit (GPU), anaccelerated processing unit (APU), a microprocessor, a microcontroller,a digital signal processor (DSP), a field-programmable gate array(FPGA), an application-specific integrated circuit (ASIC), or anothertype of processing component. In some implementations, processor 320includes one or more processors capable of being programmed to perform afunction. Memory 330 includes a random access memory (RAM), a read onlymemory (ROM), and/or another type of dynamic or static storage device(e.g., a flash memory, a magnetic memory, and/or an optical memory) thatstores information and/or instructions for use by processor 320.

Storage component 340 stores information and/or software related to theoperation and use of device 300. For example, storage component 340 mayinclude a hard disk (e.g., a magnetic disk, an optical disk, amagneto-optic disk, and/or a solid state disk), a compact disc (CD), adigital versatile disc (DVD), a floppy disk, a cartridge, a magnetictape, and/or another type of non-transitory computer-readable medium,along with a corresponding drive.

Input component 350 includes a component that permits device 300 toreceive information, such as via user input (e.g., a touch screendisplay, a keyboard, a keypad, a mouse, a button, a switch, and/or amicrophone). Additionally, or alternatively, input component 350 mayinclude a sensor for sensing information (e.g., a global positioningsystem (GPS) component, an accelerometer, a gyroscope, and/or anactuator). Output component 360 includes a component that providesoutput information from device 300 (e.g., a display, a speaker, and/orone or more light-emitting diodes (LEDs)).

Communication interface 370 includes a transceiver-like component (e.g.,a transceiver and/or a separate receiver and transmitter) that enablesdevice 300 to communicate with other devices, such as via a wiredconnection, a wireless connection, or a combination of wired andwireless connections. Communication interface 370 may permit device 300to receive information from another device and/or provide information toanother device. For example, communication interface 370 may include anEthernet interface, an optical interface, a coaxial interface, aninfrared interface, a radio frequency (RF) interface, a universal serialbus (USB) interface, a Wi-Fi interface, a cellular network interface, orthe like.

Device 300 may perform one or more processes described herein. Device300 may perform these processes based on processor 320 executingsoftware instructions stored by a non-transitory computer-readablemedium, such as memory 330 and/or storage component 340. Acomputer-readable medium is defined herein as a non-transitory memorydevice. A memory device includes memory space within a single physicalstorage device or memory space spread across multiple physical storagedevices.

Software instructions may be read into memory 330 and/or storagecomponent 340 from another computer-readable medium or from anotherdevice via communication interface 370. When executed, softwareinstructions stored in memory 330 and/or storage component 340 may causeprocessor 320 to perform one or more processes described herein.Additionally, or alternatively, hardwired circuitry may be used in placeof or in combination with software instructions to perform one or moreprocesses described herein. Thus, implementations described herein arenot limited to any specific combination of hardware circuitry andsoftware.

The number and arrangement of components shown in FIG. 3 are provided asan example. In practice, device 300 may include additional components,fewer components, different components, or differently arrangedcomponents than those shown in FIG. 3. Additionally, or alternatively, aset of components (e.g., one or more components) of device 300 mayperform one or more functions described as being performed by anotherset of components of device 300.

FIG. 4 is a flow chart of an example process 400 for allocating serviceprovider resources based on a capacity to provide the service. In someimplementations, one or more process blocks of FIG. 4 may be performedby marketplace platform 225. In some implementations, one or moreprocess blocks of FIG. 4 may be performed by another device or a groupof devices separate from or including marketplace platform 225, such asservice provider device 210 or monitoring device 220.

As shown in FIG. 4, process 400 may include identifying a service thatis provided within a region (block 410). For example, marketplaceplatform 225 may identify the service. In some implementations,marketplace platform 225 identifies the service based on the servicebeing included within a data structure associated with marketplaceplatform 225, based on receiving an identifier associated with theservice, based on receiving a user input, and/or the like.

According to some implementations, a service may include any action orinteraction that may be purchased or received by an individual (e.g.,via a service provider or service provider equipment). In someimplementations, the service may include a banking service (e.g., abanking account service, an ATM service, a transaction card service(e.g., to request or receive a new transaction card), an investmentbanking service, a loan service, and/or the like). Additionally, oralternatively, the service may include a healthcare service, a legalservice, an accounting service, an emergency response service, asecurity service, and/or the like.

According to some implementations, a region may correspond to an area orlocation that is serviced by a service provider organization.Accordingly, the region may be a geographical area, a building, acampus, and/or the like. In some implementations, the region maycorrespond to a particular town, city, county, state, country, and/orthe like.

Marketplace platform 225 may identify the service that is provided inthe region based on monitoring devices associated with a particularservice location and/or receiving information with a particular servicelocation. In some implementations, marketplace platform 225 maydetermine the region from locations of the service locations. Forexample, marketplace platform 225 may identify geographical coordinatesof the service locations and determine the region based on thegeographical coordinates and a particular range or distance from thegeographical coordinates.

In this way, marketplace platform 225 may identify a service that isprovided within a region to enable marketplace platform 225 to identifya model associated with the service.

As further shown in FIG. 4, process 400 may include identifying a modelthat is associated with the service, where the model is trained based onconsumer profile data relating to consumers that have received theservice in the region, service provider data associated with serviceproviders that have provided the service in the region, and historicalinformation associated with providing the service; (block 420). Forexample, marketplace platform 225 may identify the model associated withthe service. In some implementations, marketplace platform 225 mayidentify the model based on identifying a service that is provided in aregion, based on receiving a request (e.g., from service provider device210), based on receiving a user input, based on an event (e.g., currentdemand for the service reaches a threshold, an update to the model, achange in data to the model, and/or the like), and/or the like.

Consumer profile data includes data relating to consumers that havereceived the service in the region. For example, the consumer profiledata may include, for each consumer that received the service in theregion, a number of times the consumer received the service, timesand/or dates that the consumer received the service, a service providerand/or service provider equipment that provided the service, feedbackassociated with the provided service, and/or the like. In someimplementations, marketplace platform 225 may maintain a consumerprofile data structure, to store consumer profile data, that is updated(e.g., periodically or aperiodically) as consumers receive the servicewithin the region.

Service provider data includes data associated with service providersthat have provided the service in the region. For example, the serviceprovider data may include, for each service provider (and/or serviceprovider equipment), a number of times that the service providerprovided the service, times and/or dates that the service providerprovided the service, a consumer that received the provided service,service provider equipment used to provide the equipment, and/or thelike. In some implementations, marketplace platform 225 may maintain aservice provider data structure, to store service provider data, that isupdated as service providers provide the service in the region.

Historical information associated with providing the service may includeinformation about the service being provided outside of the region. Forexample, historical information may provide information associated witha region that is larger than the region associated with the consumerdata and/or the service provider data. As such, the historicalinformation may provide high level information associated with theservice. For example, the historical information may include when theservice was initially provided, a frequency at which the service hasbeen provided (e.g., over time or during certain time periods), and/orthe like.

In some implementations, marketplace platform 225 may train and/orimplement machine learning to train the model. In some implementations,marketplace platform 225 may receive the model and/or receiveinformation associated with the model. According to someimplementations, the model may be any model that can be trained and/orupdated according to changes in the consumer profile data, the serviceprovider data, and/or the historical information (which may be referredto herein as “the data sets”). The data sets may include millions,billions, or trillions of data points regarding the service. As such,the model may be trained using such large data sets that cannot beprocessed objectively by a human individual.

In some implementations, the model may be a model that is trained usingmachine learning. The model may implement data cleansing (e.g., toobtain and/or preprocess the consumer profile data, service providerdata, and/or historical information), (un)supervised training (which maysplit the data sets (e.g., as a whole or individually) for trainingpurposes between test sets, validation sets, and training sets),classification, and/or other machine learning elements. The model may becreated using a logistic regression, a Naïve Bayesian classifier, and/ora support vector machine (SVM) classifier. In some implementations, themodel may include a natural language processing model (e.g., to identifyterms or words associated with providing a service in the data sets)

According to some implementations, the model may be trained to identifytrends that indicate past demand for the service using the consumerprofile data, the service provider data, and the historical information.For example, the trends may identify recurrences within the data (e.g.,during certain time periods). For example, the model may identifyconsumer trends in consumer profile data relating to consumers that havereceived the service in the region, service provider trends in serviceprovider data associated with service providers that have provided theservice in the region, and/or historical trends in the historicalinformation.

In some implementations, the model may be trained to estimate a numberof times the service is to be provided during a time period (e.g., afuture time period). For example, using a current demand, marketplaceplatform 225 may refer to the model to predict a future demand for theservice during the time period.

In this way, marketplace platform 225 may identify or obtain a modelassociated with the service and/or determining or predicting a demandassociated with the service.

Although FIG. 4 shows example blocks of process 400, in someimplementations, process 400 may include additional blocks, fewerblocks, different blocks, or differently arranged blocks than thosedepicted in FIG. 4. Additionally, or alternatively, two or more of theblocks of process 400 may be performed in parallel.

FIG. 5 is a flow chart of an example process 500 for allocating serviceprovider resources based on a capacity to provide the service. In someimplementations, one or more process blocks of FIG. 5 may be performedby marketplace platform 225. In some implementations, one or moreprocess blocks of FIG. 5 may be performed by another device or a groupof devices separate from or including marketplace platform 225, such asservice provider device 210 or monitoring device 220. In someimplementations, process 500 may be performed based on results ofprocess 400, in parallel with process 400, and/or after process 400.

As shown in FIG. 5, process 500 may include determining a current demandassociated with the service in the region (block 510). For example,marketplace platform 225 may determine the current demand for theservice. In some implementations, marketplace platform 225 determinesthe current demand based on usage or a rate of providing the servicesatisfying a threshold, based on an event (e.g., an environmentalevent), based on a request from a service location and/or serviceprovider device 210, based on a user input, and/or the like.

A current demand may reflect a rate at which a service is currentlybeing provided to consumers. According to some implementations, thecurrent demand may be determined based on real-time usage dataassociated with service providers that are currently providing theservice in the region. The example real-time usage data may indicatecurrent usage (e.g., within milliseconds) of one or more transactionterminals, service provider equipment, and/or service provider device210 associated with the service. For example, a percentage oftransaction terminals, service provider equipment, and/or serviceprovider devices 210 in use may indicate a corresponding current demand(e.g., depending on the service). As such, in some implementations,marketplace platform 225 may obtain the real-time usage data mayvirtually immediately from monitoring devices 220 (e.g., via statusindicators indicating that transaction terminal or other serviceprovider equipment that is in use is active or inactive) to determinethe current demand.

In some implementations, marketplace platform 225 may use real-timeenvironment data to determine current demand. In some implementations,the environment data may be received from monitoring devices 220 and/orservice provider devices 210. As an example, monitoring device 220 mayprovide traffic information associated with traffic within the region.If the traffic information indicates a high density of traffic withinthe region, depending on the service, the high density may indicate ahigher or lower current demand for the service.

In some implementations, marketplace platform 225 may use a model (e.g.,a machine learning model as described herein) to determine the currentdemand. As such, real-time usage data and/or real-time environment datamay be tracked and/or updated according to the model to determine thecurrent demand. In some implementations, the model to determine thecurrent demand may include a natural language processing model toidentify key terms, words, or phrases associated with the service (e.g.,from social media feeds, breaking news feeds, and/or the like).

In this way, marketplace platform 225 may determine a current demand forthe service to enable the marketplace platform to predict a futuredemand for the service.

As further shown in FIG. 5, process 500 may include predicting, usingthe model and based on the current demand associated with the service, afuture demand for the service during a time period (block 520). Forexample, marketplace platform 225 may predict the future demand. In someimplementations, marketplace platform 225 may predict the future demandbased on determining the current demand, based on an event occurring,based on receiving a user input, and/or the like.

A future demand corresponds to a demand for the service during a futuretime period. The future time period may be a quantity of hours from acurrent time period, a quantity of days from a current time period, aquantity of weeks from a current time period, a quantity of months froma current time period, and/or the like. The future demand may correspondto a number of times that the service is to be provided during the timeperiod, and/or a rate at which the service is to be provided during thetime period.

In some implementations, to determine the future demand, marketplaceplatform 225 may determine characteristics of the current demand for theservice and predict the future demand using the model and based on thecharacteristics of the current demand. In such instances, thecharacteristics may correspond to a time (e.g., time of year, time ofmonth, time of week, time of day, and/or the like), a location (e.g., alocation of or within the region), environmental factors associated withthe current demand (e.g., weather, traffic, news, social media trends,and/or the like). For example, the characteristics of the current demandmay correspond to characteristics of a past demand identified or learnedby the model. The marketplace platform 225, using the model andinformation corresponding to a time period associated with the pastdemand, may predict a similar demand for the future demand (or at leasta demand based on the past demand). As such, the marketplace platform225 may use the model to predict the future demand based on thecharacteristics of the current demand.

In some implementations, marketplace platform 225 may predict the futuredemand based on a prediction model (e.g., linear regression, logisticregression, a decision tree, a random forest, a gradient boosting, aneural network, and/or the like). Additionally, or alternatively,marketplace platform 225 may utilize a machine learning model to predictthe future demand. As such, the data sets, the current demand, and/orenvironment data may be trained within the model to predict the futuredemand.

In this way, marketplace platform 225 may predict a future demand forthe service during a time period to permit marketplace platform 225 todetermine whether a current capacity to provide the service can handlethe future demand.

As further shown in FIG. 5, process 500 may include determining acurrent capacity to provide the service based on real-time serviceprovider information associated with service providers that areproviding the service in the region (block 530). For example,marketplace platform 225 may determine the current capacity to providethe service. In some implementations, marketplace platform 225determines the current capacity based on predicting the future demand.

A capacity to provide the service refers to an amount of serviceprovider resources, of a service provider organization, that areallocated to provide a service. Accordingly, a current capacity toprovide a service may correspond to a current allocation of serviceprovider resources, including service providers and/or service providerequipment capable of providing the service.

In some implementations, marketplace platform 225 may determine thecurrent capacity based on real-time service provider information fromservice providers that are currently providing the service in theregion. For example, marketplace platform 225 may determine an amount ofservice provider resources that are providing the service based oninformation from monitoring devices 220 (e.g., based on transactionterminal usage) and/or information from service provider devices 210.Additionally, or alternatively, marketplace platform 225 may maintain aschedule associated with service provider resources that are providingthe service. As such, marketplace platform 225 may refer to the scheduleto identify an amount of service provider resources providing theservice.

In this way, marketplace platform 225 may determine the current capacityto provide the service to enable marketplace platform 225 to perform anaction based on the future demand for the service and the currentcapacity to provide the service.

As further shown in FIG. 5, process 500 may include performing an actionassociated with the service based on the future demand for the serviceand the current capacity to provide the service (block 540). Forexample, marketplace platform 225 may perform the action. In someimplementations, marketplace platform 225 may perform the action basedon determining the future demand for the service, determining thecurrent capacity to provide the service, and/or the like.

In some implementations, marketplace platform 225 may perform an actionthat includes comparing the future demand for the service and thecurrent capacity to provide the service (e.g., in order to determine ifthe current capacity is sufficient to meet the future demand, todetermine if the current capacity is excessive relative to the futuredemand, and/or the like). For example, when marketplace platform 225determines that the future demand for the service exceeds the currentcapacity to provide the service, marketplace platform 225 may identifyone or more additional service providers that are available to providethe service in the region. In such cases, marketplace platform 225 mayperform an action that includes sending a notification (e.g., serviceprovider device 210) to the one or more additional service providers tobe available to provide the service in the region.

According to some implementations, a notification may include a message,file, attachment, calendar invite, image, and/or the like. In someimplementations, a notification may cause service provider device 210 topopulate a calendar with an appointment, cause service provider device210 to provide an alert (e.g., flash a light of service provider device210, activate a vibration mechanism of service provider device 210, emita sound from a speaker of service provider device 210, and/or the like),cause service provider device 210 to indicate a time and/or location forproviding the service, cause service provider device 210 to navigate aservice provider to a location to provide the service, and/or the like.In some implementations, a notification may include an offer or request,which may be displayed via service provider device 210, for a serviceprovider to provide a service. In such cases, the offer or request mayinclude an employment agreement or a service agreement that indicatescompensation for providing the service.

Furthermore, in some implementations, marketplace platform 225 mayperform an action that includes causing an account (e.g., a financialaccount, a rewards account, and/or the like) to be credited (e.g., withcurrency, with rewards points, and/or the like) for providing theservice. In such cases, marketplace platform 225 may authorize such atransaction based on receiving a confirmation from service providerdevice 210 and/or service provider equipment that a service wascompleted.

In some implementations, a notification may cause an autonomous vehicleto go to a location (e.g., to pick one or more service providers orservice provider equipment, to facilitate providing the service, and/orthe like), cause a UAV to go to a location, and/or the like.Accordingly, marketplace platform 225 may perform an action thatincludes automatically controlling one or more machines of the one ormore additional service providers (e.g., service provider equipment) torelocate to a particular location of the region to facilitate providingthe service during the time period. In some implementations, marketplaceplatform 225 may determine a location of interest for providing theservice within the region. For example, the location of interest may bedetermined based on the future demand for the service and locations ofproviding the service indicated in the consumer profile data, locationsof providing the service in the service provider data, and/or locationsof providing the service in the historical information. As such, usinglocation information from the data sets of the model, marketplaceplatform 225 may determine a relatively optimal location for serviceprovider equipment and/or service providers to provide a service withinthe region.

In some implementations, marketplace platform 225 may cause deploymentof the service provider equipment using one or more of an address,navigational instructions, traffic information, and/or the like. In someimplementations, marketplace platform 225 may determine a departure timeand/or arrival time for the service provider equipment based on the timeperiod associated with the future demand and/or a distance between theservice provider equipment and the location of interest.

In some implementations, marketplace platform 225 may perform an actionthat includes identifying one or more potential additional serviceproviders that may provide the service but are not qualified to providethe service (e.g., due to lack of experience, lack of being certified,and/or the like. In such cases, marketplace platform 225 may transmitqualification information to the one or more potential additionalservice providers to enable the one or more additional service providersto be qualified and available to provide the service during the timeperiod. For example, marketplace platform 225 may obtain qualificationinformation (e.g., from a website, from certification database, and/orthe like) and provide the qualification information to service providerdevice 210. In such cases, the qualification information may identifythe needed certification, may include information associated with aclass (e.g., in person class, online class, and/or the like) to becomecertified, may include time or location for the class, and/or the like.

In some implementations, when marketplace platform 225 determines thatthe current capacity to provide the service exceeds the future demandfor the service, marketplace platform 225 may identify one or moreservice providers that are providing the service in the region. In suchcases, marketplace platform 225 may notify the one or more of theservice providers to cease providing the service in the region. Forexample, marketplace platform 225 may send a notification to serviceprovider device 210, instructing service provider device 210 to ceaseproviding the service. In some implementations, marketplace platform 225may cause service provider equipment (e.g., autonomous vehicles,autonomous UAVs, and/or the like) to return to a storage location. Forexample, marketplace platform 225 may provide an address and/ornavigation instructions to reach the storage location in a similarmanner as providing the address and navigation instructions to thelocation of interest to provide the service.

In this way, marketplace platform 225 may perform an action based on thefuture demand for the service and the current capacity to provide theservice.

Although FIG. 5 shows example blocks of process 500, in someimplementations, process 500 may include additional blocks, fewerblocks, different blocks, or differently arranged blocks than thosedepicted in FIG. 5. Additionally, or alternatively, two or more of theblocks of process 500 may be performed in parallel.

According to some implementations described herein, a marketplaceplatform enables a service provider organization to scale serviceprovider resources (e.g., service providers and/or service providerequipment) according to a determined demand (e.g., future demand) forthe service. As such, a model and current demand (which may be based onreal-time usage and/or environmental factors) may be used to determine afuture demand for the service. Based on the future demand, and a currentcapacity of the service provider organization, the service providerorganization may either increase or decrease service provider resources(e.g., within a particular region). As such, some implementations enablea service provider organization to provision enough service providerresources to meet the needs of consumers while avoiding over staffingand/or over deploying service provider equipment to provide the service.Accordingly, the service provider organization may increase revenueand/or profits and meet the needs of potential consumers whileconserving computing resources, network resources, power resources,and/or hardware resources used to provide the service.

The foregoing disclosure provides illustration and description, but isnot intended to be exhaustive or to limit the implementations to theprecise form disclosed. Modifications and variations are possible inlight of the above disclosure or may be acquired from practice of theimplementations.

As used herein, the term component is intended to be broadly construedas hardware, firmware, or a combination of hardware and software.

Some implementations are described herein in connection with thresholds.As used herein, satisfying a threshold may refer to a value beinggreater than the threshold, more than the threshold, higher than thethreshold, greater than or equal to the threshold, less than thethreshold, fewer than the threshold, lower than the threshold, less thanor equal to the threshold, equal to the threshold, or the like.

It will be apparent that systems and/or methods, described herein, maybe implemented in different forms of hardware, firmware, or acombination of hardware and software. The actual specialized controlhardware or software code used to implement these systems and/or methodsis not limiting of the implementations. Thus, the operation and behaviorof the systems and/or methods were described herein without reference tospecific software code—it being understood that software and hardwarecan be designed to implement the systems and/or methods based on thedescription herein.

Even though particular combinations of features are recited in theclaims and/or disclosed in the specification, these combinations are notintended to limit the disclosure of possible implementations. In fact,many of these features may be combined in ways not specifically recitedin the claims and/or disclosed in the specification. Although eachdependent claim listed below may directly depend on only one claim, thedisclosure of possible implementations includes each dependent claim incombination with every other claim in the claim set.

No element, act, or instruction used herein should be construed ascritical or essential unless explicitly described as such. Also, as usedherein, the articles “a” and “an” are intended to include one or moreitems, and may be used interchangeably with “one or more.” Furthermore,as used herein, the term “set” is intended to include one or more items(e.g., related items, unrelated items, a combination of related andunrelated items, etc.), and may be used interchangeably with “one ormore.” Where only one item is intended, the term “one” or similarlanguage is used. Also, as used herein, the terms “has,” “have,”“having,” or the like are intended to be open-ended terms. Further, thephrase “based on” is intended to mean “based, at least in part, on”unless explicitly stated otherwise.

What is claimed is:
 1. A method, comprising: determining, by a device, acurrent demand associated with a service that is provided within aregion; identifying, by the device, a model that is associated with theservice, the model being trained based on: consumer profile datarelating to consumers that have received the service in the region,service provider data associated with service providers that haveprovided the service in the region, and historical informationassociated with the service providers providing the service in theregion, the model being trained using machine learning including atleast one of: data cleansing, unsupervised training, or classification,and the model being created using at least one of: a logisticregression, a Naïve Bayesian classifier, or a support vector machine(SVM) classifier; determining, by the device using the model that isassociated with the service and based on the current demand associatedwith the service, a predicted future demand for the service during atime period; determining, by the device, a current capacity to providethe service based on real-time service provider information associatedwith service providers that are providing the service in the region;determining, by the device, whether the predicted future demand for theservice exceeds the current capacity to provide the service or whetherthe current capacity to provide the service exceeds the predicted futuredemand for the service; and causing, by the device, one or more machinesto relocate to a particular location of the region to facilitateproviding the service during the time period when the predicted futuredemand for the service exceeds the current capacity to provide theservice.
 2. The method of claim 1, further comprising: obtainingreal-time usage data associated with the service providers that areproviding the service in the region; obtaining environment dataassociated with the region, the environment data indicating one or moreenvironmental factors that affect the service in the region; anddetermining the current demand based on the real-time usage data and theenvironment data.
 3. The method of claim 1, wherein the one or moremachines include at least one of: an autonomous vehicle, an unmannedaerial vehicle, a portable kiosk, or a transaction terminal.
 4. Themethod of claim 1, further comprising: receiving historical informationassociated with the service provided in a region larger than the regionassociated with the service, and determining the predicted future demandbased upon the historical information.
 5. The method of claim 1, furthercomprising: determining that the predicted future demand for the serviceexceeds the current capacity to provide the service; identifying one ormore additional service providers that are available to provide theservice in the region; and transmitting a notification to the one ormore additional service providers to be available to provide the servicein the region.
 6. The method of claim 5, wherein the historicalinformation associated with providing the service is associated with aregion that is larger than the region associated with the service. 7.The method of claim 1, further comprising: using a machine learningmodel to determine the current demand, the machine learning modelincluding a natural language processing model to identify key terms,words, or phrases associated with the service.
 8. A device, comprising:one or more memories; and one or more processors, communicativelycoupled to the one or more memories, to: determine a current demandassociated with a service that is provided within a region; identify amodel that is associated with the service, the model being trained basedon: consumer profile data relating to consumers that have received theservice in the region, service provider data associated with serviceproviders that have provided the service in the region, and historicalinformation associated with the service providers providing the servicein the region, the model being trained using machine learning includingat least one of: data cleansing, unsupervised training, orclassification, and the model being created using at least one of: alogistic regression, a Naïve Bayesian classifier, or a support vectormachine (SVM) classifier; determine, using the model that is associatedwith the service and based on the current demand associated with theservice, a predicted future demand for the service during a time period;obtain real-time usage data associated with service providers that areproviding the service in the region to determine a current capacity;determine whether the predicted future demand for the service exceedsthe current capacity to provide the service or whether the currentcapacity to provide the service exceeds the predicted future demand forthe service; and cause one or more machines to relocate to a particularlocation of the region to facilitate providing the service during thetime period when the predicted future demand for the service exceeds thecurrent capacity to provide the service.
 9. The device of claim 8,wherein the one or more processors, when predicting the predicted futuredemand, are to: predict the predicted future demand based on aprediction model, the prediction model including at least one of: alinear regression model, a logistic regression model, a decision treemodel, a random forest model, a gradient boosting model, or a neuralnetwork model.
 10. The device of claim 8, wherein the one or moremachines include at least one of: an autonomous vehicle, an unmannedaerial vehicle, a portable kiosk, or a transaction terminal.
 11. Thedevice of claim 8, wherein the one or more processors, when causing theone or more machines to relocate to the particular location of theregion, are to: cause the one or more machines to relocate to theparticular location of the region using at least one of: an address, ornavigational instructions.
 12. The device of claim 8, wherein the one ormore processors are further to: determine that the predicted futuredemand for the service exceeds the current capacity to provide theservice; identify one or more additional service providers that arewithin a particular range of the region and are unqualified to providethe service; and transmit qualification information to the one or moreadditional service providers to enable the one or more additionalservice providers to be qualified and available to provide the serviceduring the time period.
 13. The device of claim 8, wherein the one ormore processors are further to: identify one or more potentialadditional service providers that may provide the service; and providequalification information to the one or more potential additionalservice providers.
 14. The device of claim 13, wherein the one or moreprocessors are further to: obtain the qualification information from awebsite or a certification database, the qualification informationincluding at least one of: information identifying a neededcertification, or information associated with a class to becomecertified.
 15. A non-transitory computer-readable medium storinginstructions, the instructions comprising: one or more instructionsthat, when executed by one or more processors, cause the one or moreprocessors to: determine a current demand associated with a service thatis provided within a region, the current demand being based on real-timeusage data associated with service providers that are currentlyproviding the service in the region; identify a model that is associatedwith the service, the model being trained based on: consumer profiledata relating to consumers that have received the service in the region,service provider data associated with service providers that haveprovided the service in the region, and historical informationassociated with the service providers providing the service in theregion, the model being trained using machine learning including atleast one of: data cleansing, unsupervised training, or classification,and the model being created using at least one of: a logisticregression, a Naïve Bayesian classifier, or a support vector machine(SVM) classifier; determine, using the model that is associated with theservice and based on the current demand associated with the service, apredicted future demand for the service during a time period; determinea current capacity to provide the service based on real-time serviceprovider information associated with service providers that areproviding the service in the region; determine whether the predictedfuture demand for the service exceeds the current capacity to providethe service or whether the current capacity to provide the serviceexceeds the predicted future demand for the service; and cause one ormore machines to relocate to a particular location of the region tofacilitate providing the service during the time period when thepredicted future demand for the service exceeds the current capacity toprovide the service.
 16. The non-transitory computer-readable medium ofclaim 15, wherein the one or more instructions, when executed by the oneor more processors, further cause the one or more processors to: obtainenvironment data associated with the region, the environment dataindicating one or more environmental factors that affect the service inthe region; and determine the current demand based on the real-timeusage data and the environment data.
 17. The non-transitorycomputer-readable medium of claim 15, wherein the one or more machinesinclude at least one of: an autonomous vehicle, an unmanned aerialvehicle, a portable kiosk, or a transaction terminal.
 18. Thenon-transitory computer-readable medium of claim 15, wherein the one ormore instructions, when executed by the one or more processors, furthercause the one or more processors to: train the model to identify trendsthat indicate past demand for the service using consumer profile data,service provider data, and historical information; and wherein, whenpredicting the predicted future demand, the one or more processors areto: predict the predicted future demand based on the trends thatindicate the past demand for the service.
 19. The non-transitorycomputer-readable medium of claim 15, wherein the one or moreinstructions, when executed by the one or more processors, further causethe one or more processors to: obtain real-time usage data associatedwith service providers that are providing the service in the region;obtain environment data associated with the region, the environment dataindicating one or more environmental factors that affect the service inthe region; and determine the current demand based on the real-timeusage data and the environment data.
 20. The non-transitorycomputer-readable medium of claim 15, wherein the one or moreinstructions, when executed by the one or more processors, further causethe one or more processors to: identify one or more additional serviceproviders that are available to provide the service in the region; andsend a notification to the one or more additional service providers tobe available to provide the service in the region.